Text Classification
Transformers
Safetensors
English
deberta-v2
nli
natural-language-inference
knowledge-distillation
srl
self-reflective-learning
biomedical-nlp
aethermind
student-model
text-embeddings-inference
Instructions to use samerzaher80/AetherMind_SRL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use samerzaher80/AetherMind_SRL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="samerzaher80/AetherMind_SRL")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("samerzaher80/AetherMind_SRL") model = AutoModelForSequenceClassification.from_pretrained("samerzaher80/AetherMind_SRL") - Notebooks
- Google Colab
- Kaggle
AetherMind_SRL Released – SRL-ANLI Round 12 Paper (DOI Inside)
#1
by samerzaher80 - opened
AetherMind_SRL is a knowledge-distilled, self-reflective Transformer designed for robust, adversarial, and clinical Natural Language Inference (NLI).
It integrates:
Knowledge Distillation (KD) from DeBERTa-v3-base
Self-Reflective Learning (SRL) loops
ANLI adversarial fine-tuning
ADNI clinical reasoning (Alzheimer’s domain)
Smart Error Buffers and structured hard-example mining
This model is the Round 12 SRL-ANLI Smart checkpoint, achieving strong generalization across SNLI/MNLI, adversarial ANLI, and clinical Alzheimer’s reasoning.
AetherMind_SRL is part of the broader AetherMind project, a multi-year effort to build an adaptive reasoning engine with human-like error correction.